Colors

Stat 365: Statistical Communication

Wednesday, April 26th

Today we will…

  • Color
  • Color Palettes
  • Accessibility with Color
  • Color is contextual, cultural, etc.

“Color used poorly is worse than no color at all” - Edward Tufte

Some (all?) of the visual attributes we have to play with1

Color

What is color? - Colm Kelleher

Color spaces1

  • A color space is mathematical model for describing color. Some common spaces include RGB, HSB, HSL, CMYK

  • RGB (red, green, blue) is the most commonly used

RGB is additive, based on light

CMYK is subtractive, based on ink

Hue1

Saturation1

Lightness1

Examples1

Hue, Saturation, Light

Hue, Saturation, Value

Cones1

HSL Cone

HSV Cone

Color Palettes

Color Palettes1

Color Orgnaization1

Adobe Color1

Color Brewer1

Color Brewer Scales

Example1

Example1

Brainstorm!

  • What types of color palettes should we use for categorical variables?
  • What if they are ordinal?
  • What about for numeric variables?

Colorblindness

Colorblindness1

1

Colorbrewer palettes can help here, too!1

Even better? Double encode!1

Color is Contextual

Color is contextual1

Color is contextual1

The Dress1

Just noticible difference1

Which central square is darker?1

Differences are relative1

Color is cultural

Color is cultural1

The Psychology of Color Infographic1

1

1

So what?1

  • Use color sparingly
  • Use color consistently
  • Design with colorblind in mind
  • Be thoughtful of tone that color conveys
  • Brand colors? Maybe pick one or maybe two

Gray is a good color!1

How can you change colors in tableau? Can you make one of the species stand out from the others?

To do

Collect Data

  • due Thursday, 4/27

Data and Methods + Table

  • due Thursday, 5/4
  • You will need to include your statistical methods.
  • REPRODUCIBILITY! Document EVERYTHING!
  • Read CwD 3.4: Tracking the Analysis

One-number Story

  • Final submission: due Thursday, 4/27 at 11:59pm

Practice in Tableau

  • Submit URLs: due Monday, 5/1 at 11:59pm

Storytelling with Data Podcast #8: The many myths of data visualization

  • For class next week